TY - GEN
T1 - 3D reconstruction using HDR-based SLAM
AU - Yeh, Chia Hung
AU - Lin, Min Hui
AU - Lu, Wei Chieh
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 3D reconstruction is the key technology to emerging technologies such as smart robotics, VR/AR/XR and autonomous driving. To enhance the robustness of our proposed 3D reconstruction system, the HDR-based SLAM is adopted in the camera pose estimation step to improve the qualitative result of geometric reconstruction. The proposed HDR-based SLAM uses the pre-calibrated inverse camera response function (CRF) to map a single RGB image into a radiance map. To exclude the influence of exposure time, normalized radiance maps independent of exposure time are used during tracking. Since ORB feature matching is the basic element of tracking and mapping in our system, the ORB descriptor patch is re-trained especially for normalized radiance maps. Experimental results have shown good performance of our system under challenging low-light environment, which helps expand the applicability of 3D reconstruction system.
AB - 3D reconstruction is the key technology to emerging technologies such as smart robotics, VR/AR/XR and autonomous driving. To enhance the robustness of our proposed 3D reconstruction system, the HDR-based SLAM is adopted in the camera pose estimation step to improve the qualitative result of geometric reconstruction. The proposed HDR-based SLAM uses the pre-calibrated inverse camera response function (CRF) to map a single RGB image into a radiance map. To exclude the influence of exposure time, normalized radiance maps independent of exposure time are used during tracking. Since ORB feature matching is the basic element of tracking and mapping in our system, the ORB descriptor patch is re-trained especially for normalized radiance maps. Experimental results have shown good performance of our system under challenging low-light environment, which helps expand the applicability of 3D reconstruction system.
UR - http://www.scopus.com/inward/record.url?scp=85082387594&partnerID=8YFLogxK
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U2 - 10.1109/APSIPAASC47483.2019.9023307
DO - 10.1109/APSIPAASC47483.2019.9023307
M3 - Conference contribution
AN - SCOPUS:85082387594
T3 - 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
SP - 1976
EP - 1980
BT - 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Y2 - 18 November 2019 through 21 November 2019
ER -